Pancreatic adenocarcinoma (PDAC) is the fourth cause of cancer-related mortality world-wide with a five-year survival rate of less than 5%. Despite multiple large-scale genetic sequencing studies, identification of predictors of treatment response and patient survival remains challenging. The advance of artificial intelligence enables us to decipher the relationship between various levels of genetic measurements and the patient outcomes, and gain a more complete picture of the disease to develop better prognostic strategies to stratify patients. We aim to develop artificial intelligence frameworks that can be applied to support clinical decision-making in prospective clinical trials and to improve patient stratification by targeting those patients that will benefit from FOLFIRINOX treatment.
This will improve treatment efficacy and reduce toxicity by withholding ineffective treatments for selected patients.